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Related papers: A Monte Carlo approach to bound Trotter error

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Over the last decade, ingenuous developments in Monte Carlo methods have enabled the unbiased estimation of adjoint-weighted reactor parameters expressed as bilinear forms, such as kinetics parameters and sensitivity coefficients. A…

Computational Physics · Physics 2024-07-09 Eric Dumonteil , Emma Horton , Andreas E. Kyprianou , Andrea Zola

Probabilistic models are proposed for bounding the forward error in the numerically computed inner product (dot product, scalar product) between of two real $n$-vectors. We derive probabilistic perturbation bounds, as well as probabilistic…

Numerical Analysis · Mathematics 2019-06-26 Ilse C. F. Ipsen , Hua Zhou

Understanding the impact of gate errors on quantum circuits is crucial to determining the potential applications of quantum computers, especially in the absence of large-scale error-corrected hardware. We put forward analytical arguments,…

Quantum Physics · Physics 2026-04-20 Eli Chertkov , Yi-Hsiang Chen , Michael Lubasch , David Hayes , Michael Foss-Feig

We numerically investigate quantum circuit elementary-gate level instantiations of the standard Quantum Phase Estimation (QPE) algorithm for the task of computing the ground-state energy of a quantum magnet; the disordered fully-connected…

Quantum Physics · Physics 2026-03-02 Elijah Pelofske , Stephan Eidenbenz

We construct numerical integrators for Hamiltonian problems that may advantageously replace the standard Verlet time-stepper within Hybrid Monte Carlo and related simulations. Past attempts have often aimed at boosting the order of accuracy…

Numerical Analysis · Mathematics 2015-04-10 Sergio Blanes , Fernando Casas , J. M. Sanz-Serna

The simulation of the expectation of a stochastic quantity E[Y] by Monte Carlo methods is known to be computationally expensive especially if the stochastic quantity or its approximation Y_n is expensive to simulate, e.g., the solution of a…

Probability · Mathematics 2023-12-06 Annika Lang , Andreas Petersson

We consider simulating an $n$-qubit Hamiltonian with nearest-neighbor interactions evolving for time $t$ on a quantum computer. We show that this simulation has gate complexity $(nt)^{1+o(1)}$ using product formulas, a straightforward…

Quantum Physics · Physics 2019-12-19 Andrew M. Childs , Yuan Su

Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating…

Applications · Statistics 2011-08-04 Yazhen Wang

Given a real matrix A with n columns, the problem is to approximate the Gram product AA^T by c << n weighted outer products of columns of A. Necessary and sufficient conditions for the exact computation of AA^T (in exact arithmetic) from c…

Numerical Analysis · Mathematics 2014-05-16 John T. Holodnak , Ilse C. F. Ipsen

Accurate simulations of vibrational molecular spectra are expensive on conventional computers. Compared to the electronic structure problem, the vibrational structure problem with quantum computers is less investigated. In this work we…

For real symmetric matrices that are accessible only through matrix vector products, we present Monte Carlo estimators for computing the diagonal elements. Our probabilistic bounds for normwise absolute and relative errors apply to Monte…

Numerical Analysis · Mathematics 2022-03-18 Eric Hallman , Ilse C. F. Ipsen , Arvind Saibaba

This work provides a rigorous and self-contained introduction to numerical methods for Hamiltonian simulation in quantum computing, with a focus on high-order product formulas for efficiently approximating the time evolution of quantum…

Quantum Physics · Physics 2025-07-16 Javier Lopez-Cerezo

We study the approximation of $\mathbb{E}f(X_T)$ by a Monte Carlo algorithm, where $X$ is the solution of a stochastic differential equation and $f$ is a given function. We introduce a new variance reduction method, which can be viewed as a…

Probability · Mathematics 2007-05-23 Ahmed Kebaier

Hamiltonian Monte Carlo can provide powerful inference in complex statistical problems, but ultimately its performance is sensitive to various tuning parameters. In this paper we use the underlying geometry of Hamiltonian Monte Carlo to…

Methodology · Statistics 2015-02-03 M. J. Betancourt , Simon Byrne , Mark Girolami

After the seminal work of R. Landauer in 1957 relating the electrical resistance of a conductor to its scattering properties, much progress has been made in our ability to predict the performance of electron devices in the DC (stationary)…

Mesoscale and Nanoscale Physics · Physics 2016-09-22 Guillermo Albareda , Damiano Marian , Abdelilah Benali , Alfonso Alarcón , Simeon Moises , Xavier Oriols

By considering the effect of varying the target radii and detector aperture width on the scattering angle in experimental Compton scattering, mathematical models were developed and subsequently incorporated into Monte Carlo simulations. By…

High Energy Physics - Experiment · Physics 2021-04-30 Assunta Sophia Felice

Trotter and linear-combination-of-unitary (LCU) are two popular Hamiltonian simulation methods. We propose Hamiltonian simulation algorithms using LCU to compensate Trotter error, which enjoy both of their advantages. By adding few gates…

Quantum Physics · Physics 2025-03-31 Pei Zeng , Jinzhao Sun , Liang Jiang , Qi Zhao

The computational cost of quantum algorithms for physics and chemistry is closely linked to the spectrum of the Hamiltonian, a property that manifests in the necessary rescaling of its eigenvalues. The typical approach of using the 1-norm…

We present several improvements to the standard Trotter-Suzuki based algorithms used in the simulation of quantum chemistry on a quantum computer. First, we modify how Jordan-Wigner transformations are implemented to reduce their cost from…

Quantum Physics · Physics 2016-12-15 M. B. Hastings , D. Wecker , B. Bauer , M. Troyer

The utility of a Markov chain Monte Carlo algorithm is, in large part, determined by the size of the spectral gap of the corresponding Markov operator. However, calculating (and even approximating) the spectral gaps of practical Monte Carlo…

Statistics Theory · Mathematics 2019-04-08 Qian Qin , James P. Hobert , Kshitij Khare
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